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by Intel
This article provides general guidelines for connecting any Intel Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers like the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel® IoT Gateways to the Microsoft Azure IoT Suite.
by The Zakies
Question answer chatbot using natural language parsing and web scrapping
by Sarah Moir
Analyzing My Music Data with Splunk
by Bill Wagner
In this post, I look at the areas where I will invest my time in the coming year.

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by Intel
This article provides general guidelines for connecting any Intel Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers like the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel® IoT Gateways to the Microsoft Azure IoT Suite.
by The Zakies
Question answer chatbot using natural language parsing and web scrapping
by Sarah Moir
Analyzing My Music Data with Splunk
by Bill Wagner
In this post, I look at the areas where I will invest my time in the coming year.

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machine-learning 

by Intel
This article provides general guidelines for connecting any Intel Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers like the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel® IoT Gateways to the Microsoft Azure IoT Suite.
by The Zakies
Question answer chatbot using natural language parsing and web scrapping
by Sarah Moir
Analyzing My Music Data with Splunk
by Stephan Ofosuhene
This article takes a look at a variety of tools available from Intel: Intel® Movidius™ Neural Compute Stick, Intel® Python Distribution for Python™, Intel® Math Kernel DNN Library, Intel® Data Analytics Acceleration Library, Intel Distribution of OpenVINO™ Toolkit
by Gary.Miller.WPF
MNIST Digit recognition in C#
by Ahmad_Awais
I’m building a custom WordPress dashboard for an enterprise client which is powered by React.js on top of Node.js with MongoDB Atlas as the database.
by Martin_Rupp
In this article we introduce the main theoretical concepts required for building an ML-based translator.
by Dmitriy Gakh
The perspectives of creating bots that write programs with two simple examples.
by Intel
Exploring Intel® Data Analytics Acceleration Library C++ Coding for Handwritten Digit Recognition
by Mahsa Hassankashi
This article also has a practical example for the neural network. You read here what exactly happens in the human brain, while you review the artificial neuron network.
by edeferia
Describes a simple implementation of a recommending system for e-commerce sites.
by Jozu MLOps
In this article, we build a Retrieval-Augmented Generation (RAG) pipeline using KitOps, integrating tools like ChromaDB for embeddings, Llama 3 for language models, and SentenceTransformer for embedding models.
by Thomas Daniels
This article describes the making of a tic tac toe player that uses neural networks and machine learning.
by Intel
This paper introduces Intel software tools recently made available to accelerate deep learning inference in edge devices (such as smart cameras, robotics, autonomous vehicles, etc.) incorporating Intel® Processor Graphics solutions across the spectrum of Intel SOCs.
by Intel
In this blog post, we highlight one particular class of low precision networks named binarized neural networks (BNNs), the fundamental concepts underlying this class, and introduce a Neon CPU and GPU implementation.
by Abdulkader Helwan
In this article, we show you how to set up an Android Studio environment that is suitable for loading and running our .tflite model.
by Phil Hopley
In this article, we will add AI to an existing ROS (Robot Operating System) House Bot.
by Aby Mammen Mathew
IoT devices needs the capability to augment the environment around them, even when sensors utilized by them break down
by Silvina Bruggia
The COVID-19 pandemic has accelerated machine learning (ML) adoption in many areas, resulting in firms increasing their ML investment and implementation efforts.
by Mohd Akram
Java Tic Tac Toe (AI based)
by Arnaldo P. Castaño
In this article we’ll adapt the VGG16 model.
by Jarek Szczegielniak
Having converted a ResNet model to the Core ML format in the previous article, in this article we’ll now use it in a simple iOS application.
by Raymond_Lo
In this post, I will show you how you can get started with OCR using the machine learning platform TensorFlow and the Intel® Distribution of OpenVINO™ Toolkit.
by Rahul_Sindhu
Steering Behaviours, Genetic Algorithms, and Neural Networks in games
by MehreenTahir
In this article we learn about how Azure Synapse Analytics and Azure Machine Learning help analyze data without extensive coding and ML experience.
by MehreenTahir
In this article we jump right into setting up an Azure Synapse workspace and Azure Synapse Studio to prepare for our machine learning analysis in the next article in the series.
by MehreenTahir
In this article we explore how to enrich our data using a pre-trained model and trigger an Auto ML experiment from a Spark table.
by Joel Ivory Johnson
How to collect vehicle information and use ML on AWS to predict and diagnose vehicle problems before they become serious
by I Love Code
An Introduction to Logistic Regression
by Ngọc Minh Trần
An introduction to the SVM and the simplified SMO algorithm
by Florian Rappl
This article describes the most important details of creating a useful bot using the Microsoft Bot Framework.
by Jeffrey T. Fritz
In this video, Jeff shows you a quick example using the TensorFlow quickstart and how the Intel Advisor can recommend some improvements to it.
by Bahrudin Hrnjica
ANNdotNET v1.0 has been released
by Intel
A complete list of these JavaScript code sample titles is provided below along with their links to instructions and code.
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating convolutional ANNs and applying them to image classification tasks.
by Andrew Kirillov
The article demonstrates usage of ANNT library for creating fully connected ANNs and applying them to different tasks.
by Habibur Rony
Basics of the rule-based chatbot, machine-learning chatbot and AI chatbot.
by Sacha Barber
Looking at Spark/Cassandra working together
by DataBytzAI
Part one of a series to demystify and democratize the magic (not) of AI
by Intel
Artificial intelligence holds greater promise in transforming clinical research.
by ASP.NET Community
In one of our project the site usage of site was very heavy and we need to migrate it to load balancing server. I have never configured the sites in
by DaveNoderer
Recommendation System for wholesale automotive sales
by Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
by Dawid Borycki
In this article, we'll demonstrate building an Arm NN-based application for an IoT device that can perform automatic trash sorting through image analysis.
by MehreenTahir
In this article we connect a local Kubernetes cluster to Azure Arc.
by MehreenTahir
In this article, we learn how to train a machine learning (ML) model on an Arc-enabled Kubernetes cluster.
by MehreenTahir
In this article we learn to deploy our model and enable inference anywhere with Azure Arc-enabled ML.
by Prakash SNP
This article shows how to build an Azure IoT Solution for water utilities Industry
by David Norton
In this article we outline the problem: our fictional CEO wants to predict taxi use to ensure taxis are available where and when customers need them.
by David Norton
In this article we explore how to view and access model data.
by David Norton
In this article we explore how to get data into Azure Synapse Analytics and build a machine learning model.
by Florian Rappl, Niki Kilbertus
Using Microsoft Azure to add advanced machine learning capabilities with connected IoT devices, which monitor activities of a baby and his or her environment.
by KristianEkman
How to build an AI which plays Backgammon
by Jesús Utrera
Second article of a series of articles introducing deep learning coding in Python and Keras framework
by Andy Allinger
Introduces data clustering and the k-means++ algorithm
by Intel
This article will explore and compare the performance of the Intel Extension for Scikit-learn and benchmark it against the stock Scikit-learn library.
by asiwel
Bezier Curve Classification Training And Validation Models Using ALGLIB
by asiwel
Bezier Curve Classification Training and Validation Models using CNTK and ALGLIB
by Mahsa Hassankashi
It is almost everything about big data.
by Intel
This article provides an overview of recent enhancements available in the BigDL 0.1.0 release (as well as in the upcoming 0.1.1 release)
by Ragesh_Hajela
In this article we look at how to modify the OpenVINO™ Notebooks repo on GitHub, retrain the same model but with a different dataset.
by raddevus
Entry in the Artificial Intelligence and Machine Learning Contest. Here's how I learned / guessed how to find spam.
by Gamil Yassin
ML algorithms based on function or type of problems they solve
by Afzaal Ahmad Zeeshan
R2 Learn, a SaaS-based end-to-end automated machine learning (AutoML) tool, makes it easy for data scientists or data engineers to get from importing a dataset, to training models and getting predictions in just a few steps.
by Anoop Pillai
Doing some 'Big Data' and building a Recommendation Engine with Azure, Hadoop and Mahout
by Scott Clayton
Build a recommendation system using collaborative filtering and matrix factorization.
by Jo Stichbury
In this article we show, a high-level, it is possible to create sophisticated AI-enabled applications that run upon memory-constrained, ultra-low power endpoint devices.
by Jarek Szczegielniak
In this article we can proceed to train our custom hot dog detection model using Apple’s Create ML.
by Sergio Virahonda
In this article we build the model API to support the prediction service.
by Intel® Nervana™ AI Academy
This article aims to explore what happens when Intel solutions support functional and logic programming languages that are regularly used for AI.
by Vladimir Dorokhov
Build a simple machine learning service with ASP.NET Core, Tensorflow and Azure Cloud
by Intel
Based on the topics covered and the examples cited in this paper, hopefully you are convinced that the technology advancements, especially those emulating the human brain and eye, are evolving at a fast pace and may soon replace the human eye.
by philoxenic
In this article, you will be up and running, and will have done your first piece of reinforcement learning.
by philoxenic
In this article, we will see what’s going on behind the scenes and what options are available for changing the reinforcement learning.
by Cisco
The Cisco Container Platform automates the repetitive functions and simplifies the complex ones so everyone can go back to enjoying the magic of containers.
by Ujwal Watgule
The Cheetah Optimizer is a nature-inspired metaheuristic algorithm designed to tackle complex optimization problems across multiple dimensions.
by chlohee
Machine Learning. What languages come to mind? R? Python? Matlab? Bet you didn't think Visual Basic.
by Scott Clayton
Detect the programming language of a code snippet using neural networks in Azure ML Studio
by Fernando de Oliveira [MCP]
What if you could predict data using a cloud-based environment? You can do it with Azure Machine Learning.
by asiwel
How to Deploy Trained Models Concurrently
by Intel
This shop-floor equipment activity monitor application is part of a series of how-to Intel Internet of Things (IoT) code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
by Nish Nishant, Marcelo Ricardo de Oliveira, Monjurul Habib, Kunal Chowdhury «IN», Shai Raiten
In the summer of 2013, CodeProject celebrated hitting 10 million members and invited various CodeProject members to host get-togethers around the world. Here are some of the goings-on at those celebrations.
by Terrence Dorsey
CodeProject wants to help women get involved and build careers in programming. What can we do? We asked some prominent female programmers, and this is what we learned.
by Omar Gameel Salem
Using Collaborative Filtering to find people who share tastes, and for making automatic recommendations based on things that other people like.
by Intel
Before you embark on a new Internet of Things project, you should consider which communication patterns are best suited to it.
by Nicolas DESCARTES
What clustering algorithm should be selected for the clustering task?
by taheretaheri
Highlights the differences in how you create an XOR network in Neuroph, Encog and JOONE
by Intel
The Intel® Joule™ module is the newest addition to a line of powerful, multi-purpose development boards from Intel®
by Philipp_Engelmann
Competing on kaggle.com for the first time
by Manning
A chapter excerpt from Programming Robots
by Jarek Szczegielniak
In this article – the first one of the series – we’ll go over some Docker basics as they apply to ML applications.
by Omar Gameel Salem
Implementation of a sophisticated spell checker that makes use of language model to consider the context in which a word occurs
by Sergio Virahonda
In this article, we’ll deep-dive into the Continuous Training code.
by Jarek Szczegielniak
In this article we'll convert a ResNet model to the Core ML format.
by sjb_strat
Create a Spam Filter Using Machine Learning
by Dawid Borycki
How to choose and convert an existing TensorFlow model to work with Arm NN and best practices for model conversion and implementing Arm NN solutions.
by Philipp_Engelmann
In this series, I want to show you how to create a simple console-based Turing machine in Python. You can check out the full source code on https://github.com/phillikus/turing_machine. In this part, I will explain the fundamental theory behind Turing machines and set up the project based on that.
by Philipp_Engelmann
How to create a Turing machine in Python - Part 2
by Sergio Virahonda
In this article series, we'll demonstrate how to take use a CI/CD pipeline - a tool usually used by developers and DevOps teams - and demonstrate how to use it to create a complete training, test, and deployment pipeline for AI that meets the requirements of level 2 in the Google MLOps Maturity
by Shweta Lodha
This article walks you through the steps required to create a custom ML model, train it and then use the same model to analyze the sales receipt.
by Jarek Szczegielniak
In this article, we’ll start applying our basic Docker knowledge while creating and running containers in the various MLng scenarios.
by Intel
This paper explains the importance of using Intel® Performance Libraries to solve a machine-learning problem such as credit risk classification.
by Arnaldo P. Castaño
In this article we’ll put together our CNN and train it for face recognition.
by Glenn Prince
This article gives you a good starting point for your own object detection projects.
by Qualcomm Technologies, Inc.
The main objective of this project is to develop an Android Application that uses a built-in camera to capture the objects on a road and use a Machine Learning model to get the prediction and location of the respective objects.
by Qualcomm Technologies, Inc.
The main objective of this project is to develop a Machine Learning model that detects the objects on the road like pedestrians, cars, motorbikes, bicycles, buses, etc.
by Ghazanfar_Ali
Clustering of 2D data Using Python and simulation in PyGame
by @Abdul Azeez Thekkekandy
This article explores Data Science lifecycles - Business Understanding, Data Understanding and Data Preparation
by Intel
In this article, we discuss our teachings about data science in a series of steps so that any product manager or business manager interested in exploring this science will be able take their first step toward becoming a data scientist or at least develop a deeper understanding of this science.
by asiwel
Data modelling and visualization using longitudinal Bezier curves
by Jarek Szczegielniak
In this article we use Visual Studio Code to edit and debug our increasingly complex code running inside a Docker container.
by Ujwal Watgule
Credit card fraud detection is an important application of machine learning techniques.
by Mahsa Hassankashi
Deep learning convolutional neural network by tensorflow python, complete and easy understanding
by Arnaldo P. Castaño
To end off this series, we will present the alternative of adapting a pre-trained CNN to the coin recognition problem we have been examining all along.
by Arnaldo P. Castaño
In this article we will go over the basics of supervised machine learning and what the training and verification phases consist of.
by Mike Lanzetta
In this post, I'll walk you through how to get one of the most popular toolkits up and running on Windows, and run through and explain some fun examples.
by Arnaldo P. Castaño
In this article we focus on the Text-to-Speech with the use of Deep Learning.
by Jesús Utrera
Third article of a series of articles introducing deep learning coding in Python and Keras framework
by Jarek Szczegielniak
In this article, we publish our NLP API service to Azure using Azure Container Instances.
by Intel
To make it easier to deploy BigDL, we created a “Deploy to Azure” button on top of the Linux (Ubuntu) edition of the Data Science Virtual Machine (DSVM)
by Scott Clayton
Train a binary classifier in Azure and then use it in a C# application.
by Intel
In this post we show how to set up a production-ready machine learning workflow with Intel® Nervana™ technology, neon, and Pachyderm.
by Jarek Szczegielniak
In this article we run an inference model for NLP using models persisted on a Docker volume.
by Raphael Mun
In this article, we’ll dive into computer vision running right within a web browser.
by Heiko Kiessling
The article describes an easy to use a wrapper for Intel's OpenCV lib with examples.
by Intel
In this article we explore oneDAL. oneDAL includes machine learning algorithms optimized for a variety of architectures, but with the same API, meaning you can use the same application code for whatever type of system your project requires.
by Ashutosh Malegaonkar
Cisco Meraki devices provide retailers with a way to leverage their existing WiFi infrastructure to obtain insights about what happens from the time a person nears their store to the time they leave.
by Intel
This article describes different methods to detect outliers in the data and how the Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize outlier detection when running it on systems equipped with Intel® Xeon® processors.
by Sudhir Kshirsagar
The availability of low cost sensors for environmental monitoring coupled with the capabilities of the Microsoft Cloud provides a set of enormous opportunities in building a solid infrastructure for smart cities.
by Ganesan Senthilvel
An interesting article on Artificial Intelligence Chat Ro(Bot) application development
by Sams Publishing
This chapter covers the core make-up and capabilities of Visual Studio 2010.
by Johnathan Ortiz-Sonnen
Deconstructing Misty's "Follow Ball" Skill
by Adnan Masood
Disucssing use of WCFSvcHost and WcfTestClient for Service hosting and testing
by Bahrudin Hrnjica
Export options in ANNdotNET
by Jarek Szczegielniak
In this article, we’ll modify our code to expose the same logic via a Rest API service.
by IAmJoshChang
By using the Firebase ML Kit, developers save small companies and individuals massive amounts of time and money that would otherwise be spent on making their own ML Model.
by Arnaldo P. Castaño
In this article, we go over the steps to detect faces in an image.
by Raphael Mun
In this article, we are going to use all that we’ve learned so far with computer vision in TensorFlow.js to try building a version of this app ourselves.
by Raphael Mun
In this article, we are going to use BodyPix, a body part detection and segmentation library, to try and remove the training step of the face touch detection.
by Grasshopper.iics
Human Activity tracking and aggregation at the edge with Activity based climate control
by Rodrigo Costa Camargos
Implement well-known agglomerative clustering algorithm in C#
by Joel Sebold
An often neglected — but ultimately fundamental — driver of financial markets is liquidity. Combining data science skills and techniques, the Refinitiv Labs Liquidity Discovery project provides in-depth market liquidity insights to enable more informed trading decisions.
by Glenn Prince
In this article, we create an object detection model.
by Mahsa Hassankashi
phenomenon prediction and simulation by Markov Chain Mont Carlo
by Raphael Mun
In this article we will build a Fluffy Animal Detector, where I will show you a way to leverage a pre-trained Convolutional Neural Network (CNN) model like MobileNet.
by Jin Choi, PhD
A layman's description of how Kalman Filters work, and sample code that shows how to use it to forecast stock market volatilities
by Jesse Casman
Do developers really need to pay attention to chatbots in a fairly small market of just over a billion dollars?
by Intel
FourDotOne digital transformation solutions running on high-performance Intel architecture are enabling industrial and automotive manufacturers to solve complex production line issues and achieve the benefits of Industry 4.0.
by Packt Publishing
How to solve real-world problems with R and Machine learning
by Alaa Ben Fatma
A visual scripting environment for R & data science
by pseudonym67
Introduction to genetic algorithms.
by pseudonym67
A Look at Adaptive Programming with Genetic Algorithms
by Raphael Mun
In this article, I will show you how quickly and easily set up and use TensorFlow.js to train a neural network to make predictions from data points.
by Intel
Theano is a Python library developed at the LISA lab to define, optimize, and evaluate mathematical expressions, including the ones with multi-dimensional arrays (numpy.ndarray)
by syed shanu
In this article, we will see how to develop our first ML.Net application to predict the Item stock quantity.
by syed shanu
In this article, we will see how to work on Clustering model for predicting the Mobile used by model, Sex, before 2010 and After 2010 using the Clustering model with ML.NET.
by King Coffee
Sample code for OpenCvSharp 3 quick start
by César de Souza
A description of how it was possible to achieve real-time face detection with some clever ideas back in 2001
by ASP.NET Community
I hosted my wcf service with wsHttpBinding as well as netTcpbinding.While I hosted with netTcpBinding on IIS 7 follwing things I have considered,
by Intel
Today we’ll take a close look at exactly how retailers are using machine learning technologies to maximize their business. To do so, we’ll talk about the application programming interface (API). If you have a technical background, chances are that you might be familiar with and using this important
by Packt Publishing
Excerpt from the book Mastering Machine Learning for Penetration Testing by Chiheb Chebbi
by Intel
This article will go over some basics of AI, and outline some tools and resources that may help.
by ASP.NET Community
To host your Web site in IIS you need to perform following steps:1. Click Start, Administrative Tools, Internet Information Services (IIS)
by ASP.NET Community
To host your Web site in IIS you need to perform following steps:1. Click Start, Administrative Tools, Internet Information Services (IIS)
by Matteo Manferdini
A guide on how to be on top of iOS development
by Intel
This home fall tracker application is part of a series of how-to Intel® Internet of Things (IoT) code sample exercises using the Intel IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
by Intel
This smart stove top application is part of a series of how-to Intel IoT code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
by Intel
This automatic watering system application is part of a series of how-to Intel IoT code sample exercises using the Intel® IoT Developer Kit, Intel® Edison development platform, cloud platforms, APIs, and other technologies.
by Intel
This access control system application is part of a series of how-to Intel® IoT Technology code sample exercises using theIntel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
by Intel
This smart alarm clock application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
by Intel
This smart doorbell application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
by Intel
This line following robot application is part of a series of how-to Intel® IoT Technology code sample exercises using the Intel® IoT Developer Kit, Intel® Edison board, cloud platforms, APIs, and other technologies.
by Mohammad A Rahman
ID3 Decision Tree Algorithm - Part 1 (Attribute Selection Basic Information)
by Intel
In this tutorial, we will setup a basic machine learning prediction model to run as an Amazon Web Services (AWS) Lambda function in an AWS Greengrass group.
by Akhil Mittal
Face recognition and detection using modern AI based Azure cognitive service
by Ravimal Bandara
An implementation of unsupervised watershed algorithm to image segmentation with histogram matching technique for reduce over-segmentation by using openCV.
by Ashkan Pourghasem
Hands on tutorial of implementing batch gradient descent to solve a linear regression problem in Matlab
by Grasshopper.iics, Abhishek Nandy, Moumita Das
Industrial IoT time series data collection with GE Predix time series ingestion and data streaming
by Intel
This guide describes the implementation of an industrial use case using Intel® IoT Gateway and the IBM Watson IoT Platform running on IBM Bluemix.
by Ngọc Minh Trần
An introduction to Infer.NET
by Intel
MXNet is an open-source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices, from cloud infrastructure to mobile devices.
by Glenn Prince
In this article, we'll set up everything we need to build a hardhat detector with OpenCV.
by Intel
Microsoft Azure collaborates with Intel IoT® Technologies to provide developers with a full set of development tools – from the edge to the cloud.
by Intel
The Developer's Introduction to Intel MKL-DNN tutorial series examines Intel MKL-DNN from a developer’s perspective. Part 1 identifies informative resources and gives detailed instructions on how to install and build the library components.
by Intel
In Part 2 we will explore how to configure an integrated development environment (IDE) to build the C++ code example, and provide a code walkthrough based on the AlexNet deep learning topology.
by Android on Intel
Intel® System Studio 2017 Beta has been released. This is the Beta program page which guides you further on Intel® System Studio 2017 Beta new features and enhanced usability experience.
by Intel
Now that the eight-week Intel® Ultimate Coder Challenge for IoT is complete, teams continue developing and expanding their projects into the commercial sector.
by Intel
Your Path to Deeper Insights
by Andy Allinger
Add features to k-means for missing data, mixed data, and choosing the number of clusters
by Yuri Diogenes
This article explores how the Microsoft Azure IoT Suite provides a secure and private Internet of Things cloud solution.
by Raphael Mun
In this article, we will take photos of different hand gestures via webcam and use transfer learning on a pre-trained MobileNet model to build a computer vision AI that can recognize the various gestures in real time.
by Glenn Prince
This article is the first in the Data Cleaning with Python and Pandas series that helps working developers get up to speed on data science tools and techniques.
by Sacha Barber
An introductory article on Apache Spark, with a demo app
by Marcelo Ricardo de Oliveira
In this article we explore Azure Synapse Analytics and some of its features.
by Marcelo Ricardo de Oliveira
In this article we explore how data science and business intelligence teams can use Azure Synapse Analytics data to gain new insight into business processes.
by Clinton Sheppard
A hands-on, step-by-step introduction to machine learning with genetic algorithms using Python.
by Thomas Daniels
In this article, let’s dive into Keras, a high-level library for neural networks.
by Mostafa Eissa
10,000 foot view of machine learning
by Akhil Mittal
In this and the following articles on Machine Learning to figure out whatMachine Learning is and what can be achieved with it
by syed shanu
Introduction to Machine Learning and ML.NET (Machine Learning.NET)
by Thomas Daniels
In this article we take a look at what you can do with the Natural Language Toolkit (NLTK).
by Thomas Daniels
In this article we take a quick look at NumPy and TensorFlow also do a short overview of the scikit-learn library.
by philoxenic
In this article, we start to look at the OpenAI Gym environment and the Atari game Breakout.
by Thomas Daniels
In this article let's get started hands-on with OpenCV.
by Intel
This paper shows how the python API of the Intel® Data Analytics Acceleration Library (Intel® DAAL) tool works. First, we explain how to manipulate data using the pyDAAL programming interface and then show how to integrate it with python data manipulation/math APIs.
by Todd Christell, Canin Christell
Creating a Microwave Oven IoT Application
by JeffHeaton
Use Encog genetic algorithms, simulated annealing, neural networks and more with HTML5 Javascript.
by Intel
This guide will help you to write complex neural networks such as Siamese networks in Keras. It also explains the procedure to write your own custom layers in Keras.
by Gaston Verelst
How to use F# to implement algorithms such of k-means
by Maya Natarajan
Are you ready to discover new opportunities with knowledge graphs? Download the book today and let us know what you think.
by philoxenic
In this article we will learn from the contents of the game’s RAM instead of the pixels.
by philoxenic
In this article, we will see how we can improve by approaching the RAM in a slightly different way.
by philoxenic
In this article, we will see how you can use a different learning algorithm (plus more cores and a GPU) to train much faster on the mountain car environment.
by philoxenic
In this final article in this series, we will look at slightly more advanced topics: minimizing the "jitter" of our Breakout-playing agent, as well as performing grid searches for hyperparameters.
by Alibaba Cloud
This post features a basic introduction to Machine Learning. This post on Machine Learning will not only help you to understand the latest trends in the Internet industry, but increase your understanding of the technology that plays a major role in many services that make our lives easier.
by Alibaba Cloud
In this post, we learn about algorithms that help implement ML functions.
by Alibaba Cloud
This post features a basic introduction to machine learning (ML). You don’t need any prior knowledge about ML to get the best out of this article. Before getting started, let’s address this question: "Is ML so important that I really need to read this post?"
by Dmitriy Gakh
An introduction to Genetic Algorithms with brief reference to biology and example of finding one solution for complex mathematical equation
by Vietdungiitb
a library for handwriting recognition system which can recognize 99% to digit or 90% to capital letter+ digit
by Intel
Get Results with the Intel® Data Analytics Acceleration Library and the Latest Intel® Xeon Phi™ Processor
by Bahrudin Hrnjica
Linear regression with CNTK and C#
by Intel
With Litmus Automation software running on Intel architecture, manufacturers can access and analyze essential data across both legacy and modern infrastructure.
by Intel
This paper focuses on the implementation of the Indian Liver Patient Dataset classification using the Intel® Distribution for Python* on the Intel® Xeon® Scalable processor.
by Mahsa Hassankashi
Best practice for learning Basic of Machine Learning and Gradient Descent based on Linear Regression. This article will explain step by step computational matters.
by Mahsa Hassankashi
Best practice for opinion and Text Mining based on Naïve Bayesian Classifier.
by Intel
Join Intel Technical Consulting Engineer David Liu, for an overview of Intel’s Python distribution and daal4py package
by Shun Huang
Basics of ML and Perception learning algorithm
by Michael Chourdakis
An introduction to machine learning with working C++ code that trains a linear regression model.
by KristianEkman
A cell by cell walkthrough of the maths of a Neural network
by Intel
Intel is uniquely positioned for AI development—the Intel’s AI Ecosystem offers solutions for all aspects of AI by providing a unified front end for a variety of backend technologies, from hardware to edge devices.
by Akhil Mittal
This is the second article of the series and will largely focus on machine learning processes and scenarios.
by Carlos Conceição
Machine learning road to disappointment
by Intel
In this article we present MADRaS: Multi-Agent DRiving Simulator. It is a multi-agent version of TORCS, a racing simulator popularly used for autonomous driving research by the reinforcement learning and imitation learning communities
by Keith Pijanowski
In this article I provide a brief overview of Keras for those looking for a deep learning framework for building and training neural networks
by Richard Northedge
Presents a Maximum Entropy modeling library, and discusses its usage, with the aid of two examples: a simple example of predicting outcomes, and an English language tokenizer.
by Glenn Vassallo
An end to end IoT system utilising Microsoft Azure Cloud Technology and an embedded device, the Texas Instruments CC3200 LaunchPad (Single Chip Wi-Fi MCU).
by Lee Stott
The Microsoft Data Science Virtual Machine jump starts your analytics project. It enables you to work on tasks in a variety of languages including R, Python, SQL, and C#.
by Sergio Virahonda
In this article, we develop a model unit testing container.
by Sergio Virahonda
In this article, we’ll implement automatic training.
by pi19404
Supervised ML algorithm for multi-class classification
by pi19404
About single-hidden layer MLP
by Jarek Szczegielniak
In this article we run inference on sample images with TensorFlow using a containerized Object Detection API environment.
by Intel
Intel® Software Innovator Joshua Montgomery, Karl Fezer, and Steve Penrod of the Mycroft team let me pick their brains to learn a bit more about Mycroft.
by Vince Chan
A walkthrough of common machine learning tasks - by building a Naive Bayes Spam Classifier using python and scikit-learn
by Intel
Nervana is currently developing the Nervana Engine, an application specific integrated circuit (ASIC) that is custom-designed and optimized for deep learning.
by Nicolas DESCARTES
How to implement neural networks for regression in C# ?
by Ngọc Minh Trần
Diary of learning Machine Learning and TensorFlow
by Rohit_Goyal
The diversity of edge devices makes deploying applications difficult. Nutanix Xi IoT provides the developer with an environment frees them to focus on what they do best, creating applications that transform data into decisions.
by lessthanoptimal
Simple tutorial on visual object tracking with BoofCV on Android and the Desktop
by Intel
This article describes a common type of regression analysis called linear regression and how the Intel® Data Analytics Acceleration Library (Intel® DAAL) helps optimize this algorithm when running it on systems equipped with Intel® Xeon® processors.
by Stephan Ofosuhene
This post discusses strategies for improving the performance of Python applications by making them run faster and use fewer resources.
by Intel
Dispelling the Myths with Tools to Achieve Parallelism
by Keith Pijanowski
This article is the first in a series of seven articles in which we will explore the value of ONNX with respect to three popular frameworks and three popular programming languages.
by pankajdoke, SanjayKimbahune, Kushal Gore
- making version 3.2.8 of SQLite available as an extension for BREW version 3.1.2
by Prashant Gotarne, pankajdoke, SanjayKimbahune
‘Indix’ is an open source component written in C for Indian font rendering. Indix is a de facto implementation of the rules of Indian languages by CDAC.
by Intel
This project describes how to recognize certain types of human physical activities using acceleration data generated from the ADXL345 accelerometer connected to the Intel® Edison board.
by Intel
This project describes how to recognize certain types of human physical activities using acceleration data generated from the ADXL345 accelerometer connected to the Intel® Edison board.
by Arnaldo P. Castaño
In this article, we’ll talk about preparing a dataset for feeding the correct data to a CNN.
by Jarek Szczegielniak
In this article we’ll start data preparation for this new, custom model, to be later trained using the Create ML framework.
by Glenn Prince
In this article, we train our own custom model to detect if people are wearing hardhats.
by Cloud Native Apps Team
Check out this article of our series on intelligent apps to learn best practices for transitioning your on-premises or IaaS solutions to intelligent apps.
by Sergio Virahonda
In this article I’ll show you how to train your deep fake models in the cloud with some help from Docker.
by Thomas Daniels
In this article we can take a look at what libraries are available to work on AI and ML tasks.
by Thomas Daniels
This article provides some tips for experienced programmers to get up to speed with the basics of Python.
by Thomas Daniels
In this article we go a bit further with generators and classes.
by Thomas Daniels
Now that you know some of the basics of Python we can go a bit deeper, with the lists and tuples data structures and see how to work with them.
by Mahsa Hassankashi
This article provides python code for random forest, one of the popular machine learning algorithms in an easy and simple way.
by Darko Jurić
Fast object detection by template matching
by Shweta Lodha
Ways to extract information from sales receipt and detailed demonstration of how to use pre-built ML models
by Afzaal Ahmad Zeeshan
Integrate Cognitive Services SDKs in .NET Core based app
by Afzaal Ahmad Zeeshan
Integrating Cognitive Services SDKs in a .NET Core based application and exploring how real-world scenarios can be tackled using ML services offered by Microsoft
by Thomas Daniels
This article describes how to use a neural network to recognize programming languages, as an entry for CodeProject's Machine Learning and Artificial Intelligence Challenge.
by Sandeep Andre, pankajdoke, suneetachawla, SanjayKimbahune
This article attempts to elucidate how to create an application to record and play video. There is also a brief explanation of related APIs
by Intel
The Intel® AI DevJam Demo GUI uses a Windows application to communicate with a facial recognition classifier and an option of two classifiers trained to detect Invasive Ductal Carcinoma (Breast cancer) in histology images.
by George Swan
An example of how the temporal difference algorithm can be used to teach a machine to become invincible at Tic Tac Toe in under a minute
by Jarek Szczegielniak
In this article, we’ll create a container to run a CPU inference on the trained model.
by Jarek Szczegielniak
In this article, we’ll adapt our image for Raspberry Pi with an ARM processor.
by Jarek Szczegielniak
In this article we go back to the Intel/AMD CPUs. This time, we will speed up our calculations using a GPU.
by Günther M. FOIDL
Sammon's projection is a nonlinear projection method to map a high dimensional space onto a space of lower dimensionality.
by Intel
Intel’s new Deep Learning tools (with the upcoming integration of Nervana’s cloud stack) are designed to hide/reduce the complexity of strong scaling time-to-train and model deployment tradeoffs on resource-constrained edge devices without compromising the performance need.
by Dmitrii Nemtsov
A way to build a finite-state machine identifying predefined sequences in a stream of characters
by MehreenTahir
In this article, we’ll look at some advantages of serverless computing and then dig into a real-world example using the Microsoft Azure Functions service to build and deploy a sample ML inferencing function.
by Chris_Meyer
Using Azure, teach Misty to read text extracted from an image, and then return an encoded .wav file that she can save and play.
by Sergio Virahonda
In this article, we set up a cloud environment for this project.
by Jarek Szczegielniak
In this article we prepare our development environment.
by Philipp_Engelmann
Simple Linear Regression from scratch in Rust
by Ennis Ray Lynch, Jr.
This article implements a simple chatbot to attempt to pass a Turing test, which fails miserably.
by @Abdul Azeez Thekkekandy
This article describes how AI can be utilized to make a better team strategy from Manager (or Team Coach) in a live soccer game by utilizing SAP HANA and Amazon Sagemaker capabilities together.
by Wei_Li
This article lays out the performance data of software AI accelerators on Intel Xeon.
by Sau002
How to embed machine learning algorithem like extreme gradient boosting in C# app
by Intel
In this article, we will talk about criteria you can use to select correct algorithms based on two real-world machine learning problems that were taken from the well-known Kaggle platform used for predictive modeling and from analytics competitions where data miners compete to produce the best model
by Diego Stéfano
Spam detection in Scala using Deeplearning4j.
by Intel
Intel has invested in optimizing performance of Python itself, with the Intel® Distribution for Python, and has optimized key data science libraries used with scikit-learn, such as XGBoost, NumPy, and SciPy. This article gives more information on installing and using these extensions.
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Ryukkkk
Easy to implement machine learning
by Intel
There are many techniques to predict the stock price variations, but in this project, New York Times’ news articles headlines is used to predict the change in stock prices.
by Packt Publishing
An article about supervised learning
by Cloud Native Apps Team
In this four-part series, you’ll learn how to create an Intelligent App with Azure Container Apps. In this third part, you’ll explore how to level up your Intelligent Apps by training a custom model using your own dataset.
by Cloud Native Apps Team
In this four-part series, you’ll learn how to create an Intelligent App with Azure Container Apps. In this fourth and final part, you’ll explore how to integrate a custom model into your Intelligent Apps, enhancing the application’s features with specialized AI.
by philoxenic
In this article, we set up with the Bullet physics simulator as a basis for doing some reinforcement learning in continuous control environments.
by philoxenic
In this article, we look at two of the simpler locomotion environments that PyBullet makes available and train agents to solve them.
by Sau002
How to create C# applications using TensorFlowSharp
by Intel
This paper introduces the Artificial Intelligence (AI) community to TensorFlow optimizations on Intel® Xeon® and Intel® Xeon Phi™ processor-based platforms.
by Niladri_Biswas
Text Mining and its Business Applications
by dcmuggins
Bubble Sort is great...and terrible at the same time.
by Dino Konstantopoulos
Running Theano with an Nvidia 1070 GPU on Windows 10, with CUDA 8 and Visual Studio 2015
by kristofleroux
Create your own flickr diashow
by Chris_Riley
This article explores how developers can make deep-learning applications faster and more efficient by taking advantage of tools that optimize deep-learning code.
by Intel
We will train the Apache MXNet Gluon model in Amazon SageMaker to read handwritten numbers of MNIST dataset and then run the prediction for ten random handwritten numbers on IEI Tank AIoT Developer Kit.
by Glenn Prince
In this article, we begin the process of creating a custom object detection model.
by MehreenTahir
In this article we demonstrate how to train a model to detect the presence of a human in images.
by MehreenTahir
In the previous article we trained a simple machine learning model that identifies when and where a human is present in an image. This article will demonstrate how to test this model and re-train it as necessary.
by MehreenTahir
In this article we demonstrate how to deploy a Custom Vision model on a Raspberry Pi device to detect pedestrians in front of a vehicle.
by philoxenic
In this article we will try to train our agent to run backwards instead of forwards.
by philoxenic
In article in this series we will look at even deeper customisation: editing the XML-based model of the figure and then training the result.
by philoxenic
In this article in the series we start to focus on one particular, more complex environment that PyBullet makes available: Humanoid, in which we must train a human-like agent to walk on two legs.
by philoxenic
In this article we will adapt our code to train the Humanoid environment using a different algorithm: Soft Actor-Critic (SAC).
by Intel
In this blog post we will explain transfer learning and some of its applications, explain how neon can be used for transfer learning, walk through example code that uses neon for transferring a pre-trained model to a new dataset, and discuss the merits of transfer learning with some results
by Chris Maunder
Dive into the world of machine learning and explore how it empowers businesses to extract valuable insights from vast amounts of data. Discover practical techniques and tools for successful implementation.
by Nicolas DESCARTES
How to implement neural networks in C#?
by Nicolas DESCARTES
What is naive Bayes and how to implement it?
by Nicolas DESCARTES
How to implement logistic regression in ML.NET?
by Intel
To help innovators tackle the complexities of machine learning, we are making performance optimizations available to developers through familiar Intel® software tools, specifically through the Intel® Data Analytics Acceleration Library (Intel® DAAL) and enhancements to the Intel® Math Kernel Library
by sjb_strat
Use machine learning to determine the programming language of text
by Intel
This article provides general guidelines for connecting any Intel® Internet of Things (IoT) devices (that is, devices that support Intel microcontrollers, such as the Intel® Edison board and the Intel® Curie™ Compute Module) and Intel gateways to the Amazon Web Servives (AWS) IoT platform.
by Wayne Applebaum
Discussion of the issues of identifying adverse drug effects and how machine learn and big data techniques can solve for them.
by Jesús Utrera
In this article we will train the machine to compare strings using logistic regression applied to the result of using Levenshtein algorithms (adapted) and Jaro-Winkler.
by David_Oliver
In this article we look at how Refinitiv Labs looks at the real-life challenge faced by equity traders with regards to detecting and responding to unexpected asset price changes.
by Glenn Prince
In this article, we'll have a look at some of the pretrained models we can use in ImageAI to start detecting people in images.
by Pete Garcin
Exploring how to take one of the pre-trained models for TensorFlow and set it up to be executed in Go - Specifically, detecting multiple objects within any image
by Jayson DeLancey
This article is the third in the Sentiment Analysis series that uses Python and the open-source Natural Language Toolkit. In this article, we'll look at techniques you can use to start doing the actual NLP analysis.
by Thomas Weller
Demonstrates how to run Python scripts from C#
by Intel
When you connect Internet of Things (IoT) devices (devices that support Intel microcontrollers such as the Intel® Edison board, Intel® Curie™ Compute Module, and Intel® IoT gateways) to the IBM Watson* IoT Platform, you can rapidly build IoT apps that realize your IoT use case.
by Android on Intel
In this article I will explain what is DNN and how the Intel® SSSE3 instruction set helps to accelerate DNN calculation progress.
by Mr. xieguigang 谢桂纲
Machine playing snake game
by ASP.NET Community
A Web service is defined by the W3C as "a software system designed to support interoperable Machine to Machine interaction over a network." Web
by Alexandr Surkov
Principles of video analysis
by Adrian Pirvu
A closer look into differences between natural nervous systems and artificial neural networks
by David Veuve
In our last post on parsing, we detailed how you can pass URL Toolbox a fully qualified domain name or URL and receive a nicely parsed set of fields that includes the query string, top level domain, subdomains. Today, we are going to doing some analytic arithmetic on those fields.
by Peter Leow
Design and implement a simple AI agent that can learn and fight the relentless spam plague.